برنامج السكري الدقيق في قطر
Shaping the future of DAQIQ diabetes care in Qatar.
DAQIQ is a research program at Hamad Bin Khalifa University that works to improve quality of life for people living with diabetes through individualised care. We bring together data analytics, artificial intelligence and lived experience, with patients, clinicians and researchers in Qatar and beyond.
نهجنا
DAQIQ: two sides, one purpose
DAQIQ starts with people and their health data, then uses AI to turn them into insights that improve diabetes care. Those insights return to people, and the loop begins again.
People & Data
Lived experience and health data from people in Qatar living with diabetes, shared with consent.
- Long-term studies with people, families and clinics across Qatar, such as the LDQ Cohort
- Clinical, imaging, genetic and everyday data, collected with consent and ethics approval
- Patients and clinicians shaping the questions we ask, in Arabic and English
AI & Insights
Analytics and AI that turn that data into individualised care, from prevention to everyday life.
- Earlier, individualised risk prediction from many kinds of data
- Explainable AI that clinicians can question and trust
- Free tools and guides for daily life on DAQIQ Living
Tap either lobe of the loop to explore it.
Research designed in Qatar, with and for the people who live here.
بحث من قطر، مع أهلها ومن أجلهم
أثرنا
DAQIQ in numbers
What the program has produced so far. Updated with every new paper, thesis and talk.
- Publications
- 17
- Active projects
- 2
- Theses completed
- 3
- Researchers trained
- 8
- Talks
- 6
مشاريعنا
Current projects
The studies DAQIQ is running now.
شارك معنا
Help shape the future of diabetes care in Qatar.
Whether you live with diabetes, care for someone who does, treat patients, study or do research, there is a place for you in DAQIQ. Choose the option that fits you.
Taking part is always voluntary. Registering your interest means we may contact you when a study opens. It does not enrol you in any study.
الأخبار والفعاليات
News and events
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Upcoming talk: ORCHID-DR: clinical ordinal-lesion attention with semantic prototypes for robust diabetic retinopathy grading
Dr. Zubair Shah at 7th International Conference on Medical Imaging and Computer-Aided Diagnosis (MICAD 2026), Edinburgh, United Kingdom.
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Dr. Sulaiman Khan completes his PhD
His thesis used longitudinal Qatar Biobank data to predict type 2 diabetes years before it starts. He continues with DAQIQ as a Research Assistant.
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HBKU Thematic Research Grant for AI-driven proactive care
DAQIQ received USD 96,000 from the HBKU Thematic Research Grant Program for AI that monitors health signals and recommends timely care, starting in 2026.
منشوراتنا
Latest publications
- 2025
Artificial intelligence–based diabetes risk prediction from longitudinal DXA bone measurements
Khan S, Shah Z. Scientific Reports 15: 25706.
- 2025
Khan S, Biswas MR, Shah Z. Artificial Intelligence in Healthcare (AIiH 2025), Lecture Notes in Computer Science 16038, Springer.
- 2025
Early prediction of type 2 diabetes using multimodal data and tabular transformers
Khan S, Biswas MR, Shah Z. 3rd International Conference on Foundation and Large Language Models (FLLM 2025): 592–599, IEEE.
- 2025
ECG features improve multimodal deep learning prediction of incident T2DM in a Middle Eastern cohort
Mohsen F, Safa A, Shah Z. Scientific Reports 15: 27164.
- 2025
Integrating non-linear Radon transformation for diabetic retinopathy grading
Mohsen F, Belhaouari S, Shah Z. Scientific Reports 15: 30706.